How should I interpret this validation plot?
This is a sign of overfitting.

As you make your trees deeper, it becomes possible to "memorize" the data: each leaf of the tree is just a single point. The trees begin to learn patterns that do not exist. When you try out these patterns on new data (which is what cross-validation is imitating), then the patterns do not work, and your model fails to generalize.

The main piece of information to draw from this plot is that the optimum tree depth is about 15.